Demand Prediction System

Install guide

Python version : Python 3.5

Clone the repo

$ git clone https://github.com/mankar1257/CROWN_AI.git
$ cd CROWN_AI

Create the virtualenv

$ mkvirtualenv CROWN_AI

Install dependencies

$ pip install -r requirements.txt

Setting environment variables

FOR UBUNTU

Open environment file

$ sudo -H gedit /etc/environment

Add this into environment file

$ DB="mongodb+srv://CROWN_AI:1234@cluster0-eowpu.mongodb.net/<dbname>?retryWrites=true&w=majority"

Run the app

$ cd API
$ python3 app.py

Test

Using Postman

URL : http://127.0.0.1:5000/find?H=1&I=1

Using Python request

import requests

x = requests.get('http://127.0.0.1:5000/find?H=1&I=1')

x = x.json()

print(x)

Feel free to change the values of H ( Hospital ) and I (item )

Algorithms:

Auto-ARIMA, Exponential smoothing, Holt_linear Method, Holt_Winter Method,
Regression ( linear, polynomial, Lasso, Ridge, Huber, Elasticnet and SGD )

Each of these models can outperform the others on a particular dataset, so the prediction system
selects the best algorithm out of all 15 machine learning algorithms for the data.
The given data is fed to all models and the model giving the least error on the test data is selected.